Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation [PDF]
, 2011 Generalized linear mixed models are a widely used tool for modeling longitudinal data. However, their use is typically restricted to few covariates, because the presence of many predictors yields unstable estimates.
Groll, Andreas
core +5 more sources
Predicted Residual Error Sum of Squares of Mixed Models: An Application for Genomic Prediction. [PDF]
, 2017 Genomic prediction is a statistical method to predict phenotypes of polygenic traits using high-throughput genomic data. Most diseases and behaviors in humans and animals are polygenic traits. The majority of agronomic traits in crops are also polygenic.
Xu, Shizhong
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Derivative Computations and Robust Standard Errors for Linear Mixed Effects Models in lme4 [PDF]
, 2017 While robust standard errors and related facilities are available in R for many types of statistical models, the facilities are notably lacking for models estimated via lme4.
Merkle, Edgar C., Wang, Ting
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The analysis of very small samples of repeated measurements II: a modified box correction [PDF]
, 2010 There is a need for appropriate methods for the analysis of very small samples of continuous repeated measurements. A key feature of such analyses is the role played by the covariance matrix of the repeated observations.
Bellavance +22 more
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A GABAergic projection from the centromedial nuclei of the amygdala to ventromedial prefrontal cortex modulates reward behavior [PDF]
, 2016 The neural circuitry underlying mammalian reward behaviors involves several distinct nuclei throughout the brain. It is widely accepted that the midbrain dopamine (DA) neurons are critical for the reward-related behaviors.
Bhatti, Dionnet L +9 more
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Mean squared error of empirical predictor
, 2004 The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are ...
Das, Kalyan +2 more
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Penalized additive regression for space-time data: a Bayesian perspective [PDF]
, 2003 We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective.
Fahrmeir, Ludwig +2 more
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, 2021 The ranking of hybrids via genotypic values stands out due to its maximum selective accuracy in relation to ordering based on phenotypic values, which incorporate environmental effects, causing changes in the final classification.
J. S. Júnior +2 more
semanticscholar +1 more source
Likelihood inference for small variance components
, 2000 In this paper, we develop likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, we use local asymptotic approximations to construct confidence intervals for the components ...
Stern, S.E., Welsh, A.H.
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Increased heterozygosity and allele variants are seen in Texel compared to Suffolk sheep [PDF]
, 2004 In this study, the Suffolk and Texel sheep breeds were compared for microsatellite marker heterozygosity throughout seven chromosomal regions in the sheep genome.
A Farid +48 more
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